A neural network approach to classify carotid disorders from Heart Rate Variability analysis.

Affiliation

Institute of High Performance Computing and Networking (ICAR-CNR), Via Pietro Castellino, 111, Naples, Italy. Electronic address: [Email]

Abstract

Atherosclerosis is a progressive process responsible for most heart diseases and ischemic stroke. It constitutes, in fact, the most common cause of stroke in middle-aged people. To avoid or, at least, limit the disabling deficits that may derive from a carotid disease, a prompt and early diagnosis is necessary. The diagnostic technique used to detect a carotid disease is the eco-color Doppler. Unfortunately, this method is not free from errors, due to manufacturer mistakes or its operator dependence.

Keywords

Artificial neural networks,Carotid diseases,Correlation-based feature selection,HRV analysis,Signal processing,